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Demonstrates enhanced seizure data analysis in neuroscience, indicating improved workflow efficiency.
High-density multielectrode arrays (HD-MEAs) generate large, complex datasets that are challenging to efficiently manage and analyze with existing tools, especially in open-source environments. To address this, we developed the BYU Seizure and Analytics Tool (YSA), an open-source graphical user interface built in Python and C++ for efficient analysis and visualization of HD-MEA recordings. The YSA features raster plots, automated discharge detection and tracking, downsampling, playback, and export functions, enabling streamlined workflows for large-scale neural data. We demonstrate the utility of the tool in the context of seizure and status epilepticus-like activity, highlighting how the YSA facilitates rapid exploration of the spatiotemporal dynamics in brain networks. This platform provides an accessible and practical solution for HD-MEA data analysis, supporting a range of neuroscience applications.
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Blotter et al. (2026) studied this question.
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